Circulating tumour DNA and CT monitoring in patients with untreated diffuse large B-cell lymphoma: a correlative biomarker study

Abstract

Background: Diffuse large-B-cell lymphoma is curable, but when treatment fails, outcome is poor. Although imaging can help to identify patients at risk of treatment failure, they are often imprecise, and radiation exposure is a potential health risk. We aimed to assess whether circulating tumour DNA encoding the clonal immunoglobulin gene sequence could be detected in the serum of patients with diffuse large-B-cell lymphoma and used to predict clinical disease recurrence after frontline treatment.

Methods: We used next-generation DNA sequencing to retrospectively analyse cell-free circulating tumour DNA in patients assigned to one of three treatment protocols between May 8, 1993, and June 6, 2013. Eligible patients had diffuse large-B-cell lymphoma, no evidence of indolent lymphoma, and were previously untreated. We obtained serial serum samples and concurrent CT scans at specified times during most treatment cycles and up to 5 years of follow-up. VDJ gene segments of the rearranged immunoglobulin receptor genes were amplified and sequenced from pretreatment specimens and serum circulating tumour DNA encoding the VDJ rearrangements was quantitated.

Findings: Tumour clonotypes were identified in pretreatment specimens from 126 patients who were followed up for a median of 11 years (IQR 6·8-14·2). Interim monitoring of circulating tumour DNA at the end of two treatment cycles in 108 patients showed a 5-year time to progression of 41·7% (95% CI 22·2-60·1) in patients with detectable circulating tumour DNA and 80·2% (69·6-87·3) in those without detectable circulating tumour DNA (p<0·0001). Detectable interim circulating tumour DNA had a positive predictive value of 62·5% (95% CI 40·6-81·2) and a negative predictive value of 79·8% (69·6-87·8). Surveillance monitoring of circulating tumour DNA was done in 107 patients who achieved complete remission. A Cox proportional hazards model showed that the hazard ratio for clinical disease progression was 228 (95% CI 51-1022) for patients who developed detectable circulating tumour DNA during surveillance compared with patients with undetectable circulating tumour DNA (p<0·0001). Surveillance circulating tumour DNA had a positive predictive value of 88·2% (95% CI 63·6-98·5) and a negative predictive value of 97·8% (92·2-99·7) and identified risk of recurrence at a median of 3·5 months (range 0-200) before evidence of clinical disease.

Interpretation: Surveillance circulating tumour DNA identifies patients at risk of recurrence before clinical evidence of disease in most patients and results in a reduced disease burden at relapse. Interim circulating tumour DNA is a promising biomarker to identify patients at high risk of treatment failure.

Funding: National Cancer Institute and Adaptive Biotechnologies.

Figure 1. Tumor Clonotype Analysis Work flow

Step 1a. Tumor DNA was amplified using locus-specific primer sets for the immunoglobulin heavy-chain locus (IGH) complete (IGH-VDJ), IGH incomplete (IGH-DJ), and immunoglobulin kappa locus (IGK). The amplified product was sequenced, and the frequencies of the different clonotypes determined. Step 1b. Tumor clone(s) that comprised at least 5% of the B-cell repertoire were identified for analysis of minimal residual disease (ctDNA). Step 2a. ctDNA in serum samples was calculated based on the number of lymphoma molecules (cell equivalent) per 10⁶ diploid genomes (cell equivalent). The lower limit of detection was 1 lymphoma molecule per 10⁶ diploid genomes. In cases with 2 or more tumor clones, the highest frequency clone was reported. Step 2b. ctDNA was quantitatively analyzed in serial serum samples over multiple time points.

Figure 2. Patient Sample Flow Diagram

Tree diagram showing outcome of tumor clonotype analysis of pretreatment biopsy and serum specimens. One hundred and ninety-eight pretreatment samples were analyzed for tumor clonotypes and 126 patients had identifiable clones. The time to progression and overall survival of 108 patients with and without detectable interim ctDNA at the end of cycle 2 (i.e. day 1 of cycle 3) were determined by a landmark analysis. Among 107 patients who achieved complete remission at the end of treatment, the hazard risk of developing clinical progression based on detection of ctDNA was calculated using a Cox proportional hazard model.

Figure 3. Circulating Tumor DNA Time Points and Kinetics

A. Tram stop showing ctDNA outcome of patients with early progression within 6 months of treatment completion. Time starts from pretreatment. Coded identification number shown for each patient. (*) Identifies patients who received rituximab. B. Tram stop showing outcome of all patients who completed treatment and either did not progress or had progression at least 6 months after treatment. Time starts from end of treatment (EoT). Coded identification number shown for each patient. (*) Identifies patients who received rituximab. One patient recurred with a leukemic clone detected by flow cytometry (FCM). In case #177, two clonal sequences (IGH-DJ and IGK) were initially detected, but the IGK clonotype sequence (subclone) was not considered sufficiently unique to ensure a low false positive rate (< 0.001). The biopsy sample at relapse and the two previous samples only contained the IGK clonotype, which was detected after the analysis was unblinded. The case was classified as ctDNA negative for the overall analysis as the clone was intentionally not prospectively followed. This case illustrates clonal heterogeneity and the utility of following more than one clonotype. This is an area for further optimization of the technology. Two patients (#35, 62) developed single low-level positive ctDNA during surveillance and did not have clinical progression. Separate samples from the same time points were reanalyzed in both cases and were negative for ctDNA as indicated on the tram stop, suggesting these were false positive. C. Quantitative ctDNA dynamics during treatment for all patients with detectable ctDNA. D. Quantitative ctDNA dynamics for patients who recurred post-treatment (N=17). Color and symbols represent individual patient ctDNA kinetics. X-axis shows time (months) to relapse normalized to time of clinical recurrence.

Figure 4. Kaplan-Meier Outcome Estimates and Lead Time

A. Time to progression (TTP) landmark analysis based on interim ctDNA result drawn on day 1 of cycle 3 (N= 108). The TTP at 5-years was 41.7% (95% CI: 22.2% to 60.1%) and 80.2% (95% CI: 69.6% to 87.3%), respectively, for patients who were ctDNA positive and negative. B. Survival landmark analysis based on interim ctDNA result drawn on day 1 of cycle 3 (N=108). The survival at 5-years was 65% (95% CI: 42.4% to 81.1%) and 83% (95% CI: 73.1% to 89.6%), respectively, for patients with and without detectable ctDNA. C. The median (range) lead-time between detection of disease by ctDNA and CT or flow cytometry in all 15 patients who relapsed after treatment (surveillance group) was 3.5 (0 to 200) months.